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Updated: Jan 31, 2026

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
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Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

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使用腰部CT霍恩斯菲尔德单位预测骨质疏松症:七种机器学习模型的比较性能和临床影响

Akihiko Hiyama1, Daisuke Sakai2, Hiroyuki Katoh2

  • 1Department of Orthopaedic Surgery, Tokai University School of Medicine, Isehara, Kanagawa, Japan. a.hiyama@tokai.ac.jp.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
|January 30, 2026
PubMed
概括

使用腰椎计算机断层扫描 (CT) 和霍恩斯菲尔德单位 (HU) 值的机器学习模型可以有效地选骨质疏松症. K-最近的邻居 (KNN) 显示出平衡的表现,有助于在手术前脊柱手术风险评估.

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An ideal Y-Y transformer, grounded through neutral impedances, displays per-unit sequence networks akin to those of a single-phase ideal transformer when subjected to balanced positive- or negative-sequence currents. These currents do not produce neutral currents, and their associated voltage drops.
Zero-sequence currents, which are identical in magnitude and phase, generate a neutral current, resulting in voltage drops across the neutral impedance and the low-voltage winding. If the...
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